Pulse oximeters determine an oxygen saturation level of a patient's blood, or related analyte values, based on transmission/absorption characteristics of light transmitted through or reflected from a patient's tissue. In particular, pulse oximeters generally include a probe for attaching to a patient's appendage such as a finger, earlobe or nasal septum. The probe is used to transmit pulsed optical signals of at least two wavelengths, typically red and infrared, through the patient's appendage. The transmitted signals are received by a detector that provides an analog electrical output signal representative of the received optical signals. By processing the electrical signal and analyzing signal values for each of the wavelengths at different portions of the patient's pulse cycle (i.e., pulsatile signal), information can be obtained regarding blood oxygen saturation and/or other parameter values such as pulse rate, or blood pressure/blood volume related values.
Extraction of patient physiological conditions from the plethysmographic signals can be quite effective using a well positioned sensor and when the patient or subject is resting. However, motion artifacts can easily swamp the desired information (i.e., the signal of interest) included in the plethysmographic signals when the patient is moving around and/or performing muscular contractions. Other sources of artifact or ‘noise’ that can occlude the signal of interest in a plethysmographic signal include power line noise, electrical noise from other medical equipment and light contamination. Some artifacts can severely impair the signals, whereas other types can be filtered out or do not significantly effect the desired information included in the plethysmographic signals. Furthermore, depending upon the severity and type of artifacts present in the plethysmographic signals, some techniques for extracting the desired patient physiological conditions may not be appropriate and alternative techniques may need to be employed.
Filtering techniques including low pass, band pass, and high pass filtering can be used to remove noise signal components from the signal of interest where the noise signal component occupies a frequency range outside the signal of interest. More sophisticated techniques for conventional noise filtering include multiple notch filters, which are suitable for use where the noise signal component exists at multiple, distinct frequencies, all outside the frequency band of the signal of interest.
The pass band(s) of such filters are often set in relation to a fundamental frequency of the plethysmographic signal. Generally, this fundamental frequency corresponds to the heart rate of the patient. The fundamental frequency is sometimes determined by performing a Fourier transform on the time-based plethysmographic signal to generate a frequency spectrum of the signal. As may be appreciated, in the frequency spectrum, periodic signals such as a heart rate are represented as spectral peaks. Often, noise is randomly dispersed across the spectrum such that the fundamental may be determined. However, in high motion conditions, the noise signal may overwhelm the periodic signal of the heart such that the fundamental cannot be effectively determined by simple Fourier analysis.
Further, it is often the case that the frequency spectrum of the noise signal components overlaps the frequency spectrum of the signal of interest such that even if a fundamental frequency of the plethysmographic signal could be determined, high levels of artifact/noise co-exist within the frequency band of interest. That is, some sources of noise may include frequency components in the frequency band of interest. In such cases, conventional filtering techniques based solely on frequency information may be ineffective in extracting the signal of interest from noise signals.